Modelling Abrupt Alteration in Neuron Tuning Preference from Point Process Observation

Abstract

Neuronal tuning property could change abruptly in brain machine interface (BMI), which may result in the decay of the decoding performance. We propose a novel adaptive algorithm to capture the abrupt alteration of neuronal tuning preference from point process observation. Tested on synthetic neural data, the proposed adaptive algorithm succeeds in detecting the abrupt change in neuronal tuning, and contributes to a better reconstruction of kinematics than static model.